In recent years, prevalence of computers and digital cameras has enabled anybody to photograph/print pictures with ease. For this reason, it is not rare for an individual to handle a large volume of images. In such a circumstance, the sufficient quality is not always obtained for the photographed images, depending upon photographing conditions at that moment. Thus, the technology of automatically image-correcting a large volume of the images responding to respective contents and improving the image quality thereof is required.
The process of sharpening the images is often performed as one of the technologies of improving the image quality when the images photographed with digital camera, scanners or the like are displayed or printed. The technology that is called unsharp masking is widely employed as the sharpening technology (Non-patent literature 1). Upon assuming an image and an image obtained by blurring it to be f and fs, respectively, an image g sharpened like Equation (1) is obtained.g=f+λ(f−fs)  (1)
Where λ is a coefficient that is used at the moment of adding the part in which a space frequency of the image is high into an original image, namely, a coefficient for adjusting a strength of the sharpening, and the optimum value is employed for it as a result of making an trial for many images. For example, with the case of targeting artificial products such as buildings as scenes of the input images, a value that allows the strong sharpening to be added is preferably set for the coefficient for adjusting a strength of the sharpening, and on the other hand, a value that allows the weak sharpening to be added is preferably applied with the case of targeting natural products.
The method of adjusting parameters in the sharpening process according to image features in the images is also known. Patent literature 1 states that a thickness of an edge (an edge emphasizing scope) has to be adjusted responding to the features of the images when the sharpness is emphasized for the digital images by executing the edge emphasis. And, as its adjusting method, the method is described of, when the edge exists near an objective pixel, adjusting the edge emphasis by changing an emphasis radius and a weight matrix with respect to a positional relation between the thickness of the above edge and the objective pixel.